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<rss version="2.0" xmlns:atom="http://www.w3.org/2005/Atom"><channel><title>Shedding Light on Black Box Machine Learning Algorithms: Development of an Axiomatic Framework to Assess the Quality of Methods that Explain Individual Predictions · HackerPapers discussions</title><link>https://hackerpaper.kaipfister.de/p/1808.05054/</link><description>Collected HN comments and submissions linking this paper.</description><language>en</language><lastBuildDate>Mon, 02 Nov 2026 11:16:22 GMT</lastBuildDate><atom:link href="https://hackerpaper.kaipfister.de/p/1808.05054/feed.xml" rel="self" type="application/rss+xml" /><item><title>Shedding Light on Black Box Machine Learning Algorithms: Development of an Axiomatic Framework to Assess the Quality of Methods that Explain Individual Predictions — mentioned by wizzerking</title><link>https://news.ycombinator.com/item?id=17785373</link><guid isPermaLink="false">urn:hackerpapers:mention:1808.05054:17785373</guid><pubDate>Fri, 17 Aug 2018 20:18:40 GMT</pubDate><description>&lt;p&gt;Here are some that I use Shedding Light on Black Box Machine Learning Algorithms: Development of an Axiomatic Framework to Assess the Quality of Methods that Explain Individual Predictions https://arxiv.org/abs/1808.05054 Manifold: A Model-Agnostic Framework for Interpretation and Diagnosis of Machine Learning Models https://arxiv.org/abs/1808.00196 Neither are for Deep Learnng or Neural Networks&lt;/p&gt;&lt;p&gt;&lt;a href="https://hackerpaper.kaipfister.de/p/1808.05054/"&gt;Paper and discussion history&lt;/a&gt;. A mention is not an endorsement.&lt;/p&gt;</description><category>cs.LG</category></item></channel></rss>
